Subsequently, a joint adaptive normalization step is applied to adjust the image statistics of the GM and LoG maps, in order to reduce its dependency on local image content. Finally, a bivariate histogram based feature vector is computed from the marginal probability functions and independency distributions of the normalized GM and LoG maps, resulting to a fixed-size feature representation vector of 40 dimensions for an image. We used the default parameters for feature extraction, more details can be found in [1]}.
